Week 8 - Simulating Cyclone separator with Discrete Phase Modelling

Cyclone separators or simply cyclones are separation devices (dry scrubbers) that use the principle of inertia to remove particulate matter from flue gases. Cyclone separators is one of many air pollution control devices known as precleaners since they generally remove larger pieces of particulate matter. This prevents finer filtration methods from having to deal with large, more abrasive particles later on.

It is important to note that cyclones can vary drastically in their size. The size of the cyclone depends largely on how much flue gas must be filtered, thus larger operations tend to need larger cyclones. For example, several different models of one cyclone type can exist, and the sizes can range from a relatively small 1.2-1.5 meters tall (about 4-5 feet) to around 9 meters (30 feet)—which is about as tall as a three story building.

1. Four empirical models used to calculate the cyclone separator efficiency :

(1)Iozia and Leith Model :

Iozia and Leith logistic model is a modified version of Barth Model, which is developed based on force balance. The model assumes that a particle carried by the vortex endures the influence of two forces: a centrifugal force, Z and a flow resistance, W. The collection efficiency η_i of particle diameter d_pi can be calculated from

β is an expression for slope parameter derived based on the statistical analysis of experimental data of a cyclone with D = 170 0.25 m given as

and dpc is the 50% cut size given by Barth

(2)Li and Wang Model :

The Li and Wang model includes particle bounce or reentrainment and turbulent diffusion at the cyclone wall. A twodimensional analytical expression of particle distribution in the cyclone is obtained. Li and Wang model was developed based on the following assumptions:

• The radial particle velocity and the radial concentration profile are not constant for uncollected particles within the cyclone.
• Boundary conditions with the consideration of turbulent diffusion coefficient and particle bounce reentrainment on the cyclone wall are:

• The tangential velocity is related to the radius of cyclone by: uRⁿ = constant.

The concentration distribution in a cyclone is given as:

The resultant expression of the collection efficiency for particle of any size is given as

(3)Koch and Licht Model

Koch and Licht collection theory recognized the inherently turbulent nature of cyclones and the distribution of gas residence times within the cyclone. Koch and Licht described particle motion in the entry and collection regions with the additional following assumptions:

• The tangential velocity of a particle is equal to the tangential velocity of the gas flow, i.e. there is no slip in the tangential direction between the particle and the gas.
• The tangential velocity is related to the radius of cyclone by: uRⁿ = constant.

A force balance and an equation on the particles collection yields the grade efficiency η_i

G is a factor related to the configuration of the cyclone, n is related to the vortex and τ is the relaxation term.

(4)Lapple Model

Lapple model was developed based on force balance without considering the flow resistance. Lapple assumed that a particle entering the cyclone is evenly distributed across the inlet opening. The particle that travels from inlet half width to the wall in the cyclone is collected with 50% efficiency. The semi empirical relationship developed by Lapple [1] to calculate a 50% cut diameter, d_pc, is

where N_e is the number of revolutions

The efficiency of collection of any size of particle is given by

PROCEDURE:

GEOMETRY:

• Choose Fluid flow fluent and start with editing geometry.
• Import the step file of the model into spaceclaim.
• Volume extract the model so that we can analyse the fluid flow of the cyclone separator.
• Hide the previous geometry and supress physics since we are only interested with the fluid flow and not the external surface.

MESHING:

• First, before generating the mesh, assign names to the parts and boundaries in named selection
• Generate mesh of element size 8mm

SETUP:

• In this problem, the max velocity attained by the particles and air is very less as compared to the speed of sound.
• Hence, the Mach number is <<< 0.3. Hence, a pressure-based solver was used since density-based solvers are generally used for simulations with Mach no > 0.3.
• In this particular simulation, a steady state solver was used since we do not require to observe each particle at every moment.
• Observing the number of particles that have been trapped, escaped, and incomplete, is our main motive
• Furthermore, a gravity value of 9.81 m/s^2 was added in the -ve Y direction.
• The K-epsilon RNG model was used in this particular problem.
• This model is an upgradation of the standard k-epsilon model and is used mainly for swirling flows.
• Moreover, the “swirl dominated flow” option was turned on for this simulation.
• Afterwards, the discrete phase model option was turned and the settings were changed.
• Here, the air particles represent the continuous phase whereas the solid particles represent the discontinuous phase.
• These two phases can exchange mass and momentum within the flow.
• Coupled Flow – The discrete phase can influence the flow of the continuous phase
• Uncoupled Flow – The discrete phase will not have any interaction with the continuous phase
• In this particular case, the particle size is very small, it doesn’t matter which option we chose.
• The DPM interval was chosen as 10 and thus, the particle tracking data will be updated and showed on the console every 10 iterations.
• The tracking parameters and specify length scale was set to default.
• Then a new injection was created with the following parameters –
• Material – anthracite
• Particle type – inert
• Diameter distribution – uniform
• Injection type – surface
• Release from - INLET
• Velocity – 1,3,5 m/s in the x direction
• Diameter of particles – 1,3,5 microns
• Furthermore, the boundary conditions for DPM were set accordingly

Inlet – Reflect

Wall – Reflect

Outlet 1– escape

Outlet 2– trap

• The inlet was set to a velocity inlet and outlet to a pressure outlet
• The coupled scheme with “second order upwind” was used for the turbulent kinetic energy and turbulent dissipation rate
• The solution was initialised using standard initialisation and was computed from inlet.
• The problem was then run for 600 iterations and the results were observed

2. To perform an analysis on a given cyclone separator model by varying the particle diameter from 1 μm to 5 μm and calculate the separation efficiency in each case. Discuss the results. [Use both the velocity's as 3m/sec.]

CASE 1:

Velocity = 3m/s, size = 5 microns

RESIDUAL PLOT:

ANIMATION:https://drive.google.com/file/d/1JsofySRMQcuEaGvboepPVjHYiA6LUuZ6/view?usp=sharing

CASE 2:

Velocity=3m/s, Size=3microns

RESIDUAL PLOT:

ANIMATION :https://drive.google.com/file/d/1T4asrnm36nwUf1nTdsYlfa6ntJiMomHA/view?usp=sharing

CASE 3:

Velocity=3m/s,Size=1 micron

RESIDUAL PLOT:

3. To perform an analysis on a given cyclone separator model by varying the particle velocity from 1 m/sec to 5 m/sec and calculate the separation efficiency and pressure drop in each case. Discuss the results. [Use particle diameter size as 5 μm for all cases & keep flow velocity same as particle velocity]

CASE 4:

Velocity=5m/s,Size=5microns

RESIDUAL PLOT:

ANIMATION: https://drive.google.com/file/d/1663Pr7XV5i4_mq72TWt3suIgiM18jMuR/view?usp=sharing

CASE 5:

Velocity=3m/s,Size=5microns

RESIDUAL PLOT:

ANIMATION: https://drive.google.com/file/d/1IUw3yQkEhta09XehkwWHHyl7L2hoEbRq/view?usp=sharing

CASE 6:

Velocity=1m/s,Size=5 microns

RESIDUAL PLOT:

ANIMATION: https://drive.google.com/file/d/1k1oIggCrAuvPMMfEd6Y4os_G2E-x8hTU/view?usp=sharing

• Separation efficiency:

It is defined as the fraction of particles of a given size collected in the cyclone, compared to those of that size going into the cyclone. Experience shows that the separation efficiency of cyclone separator increases with increasing particle mean diameter and density; increasing gas tangential velocity; decreasing cyclone diameter; increasing cyclone length; extraction of gas along with solids through the cyclone legs.

In this case, depending upon the particle history data - Separation Efficiency is defined as the ratio of concentration that has been removed from the feed stream to the initial concentration in the feed stream. For this case ratio of the number of trapped particles to the total number of particles tracked.

Separation efficiency = no. of particles trapped / no. of particles tracked

• Pressure Drop:

Pressure drop across the cyclone is of much importance in a cyclone separator. The pressure drop significantly affects the performance parameters of a cyclone. The total pressure drop in a cyclone will be due to the entry and exit losses, and friction and kinetic energy losses in the cyclone. Normally the most significant pressure drop occurs in the body due to swirl and energy dissipation.

Pressure drop is defined as the difference in total pressure between two points of a fluid carrying network.

Pressure drop, ΔP = Total inlet pressure - Total Outlet Pressure (escape)

As the escape DPM condition is given to the outlet-top in this case, so outlet-top is considered in pressure drop calculation.

1. For varying particle diameter at 3m/s for both the velocities:

Part-1 Cases	Particle Size (m)	Particles Tracked	Particles Escaped	Particles Trapped	Separation Efficiency(η)(%)
Case-1	1e-6	156	2	154	98.71
Case-2	3e-6	156	3	153	98.07
Case-3	5e-6	156	-	156	100

2. For varying velocities at 5 micrometres:

Part-1 Cases	Velocities (m/s)	Particles Tracked	Particles Escaped	Particles Trapped	Pressure drop	Separation Efficiency(η)(%)
Case-4	1	156	4	152	2.27	97.43
Case-5	3	156	5	151	22.33	96.79
Case-6	5	156	6	150	62.38	96.15

RESULT:

• Both the parts simulated above show that Separation efficiency depends on both the diameter and velocity of the particles. As increased diameter and velocity gives increased separation efficiency.
• Velocity has a greater impact as compared to the diameter of the particle.
• Pressure drop is dependant on velocity. For constant velocity with varying diameter sizes, the pressure drop remains almost constant.
• Increased velocity causes a higher pressure drop
• From the results, it is observed that heavier particle is trapped at the bottom outlet and lighter particles are escaped at outlet 1.
• But we can also see that lighter particles also get trapped at the bottom outlet because of interaction between lighter and heavier particles and there is an exchange of inertial forces between them as a result there is a transfer of Kinetic energy from heavier particle to the lighter particle, as a result, we can observe a certain number of heavier particles escapes through the top outlet.
• The cyclone efficiency increases when particle inlet velocity is increased and the particle diameter size is increased.
• The pressure drop inside the cyclone separator increases when the inlet velocity is increased and the particle size doesn't affect the pressure drop inside the cyclone separator.